A Framework for Megascale Agent Based Model Simulations on Graphics Processing Units

Agent-based modeling is a technique for modeling dynamic systems from the bottom up. Individual elements of the system are represented computationally as agents. The system-level behaviors emerge from the micro-level interactions of the agents. Contemporary state-of-the-art agent-based modeling toolkits are essentially discrete-event simulators designed to execute serially on the Central Processing Unit (CPU). They simulate Agent-Based Models (ABMs) by executing agent actions one at a time. In addition to imposing an un-natural execution order, these toolkits have limited scalability. In this article, we investigate data-parallel computer architectures such as Graphics Processing Units (GPUs) to simulate large scale ABMs. We have developed a series of efficient, data parallel algorithms for handling environment updates, various agent interactions, agent death and replication, and gathering statistics. We present three fundamental innovations that provide unprecedented scalability. The first is a novel stochastic memory allocator which enables parallel agent replication in O(1) average time. The second is a technique for resolving precedence constraints for agent actions in parallel. The third is a method that uses specialized graphics hardware, to gather and process statistical measures. These techniques have been implemented on a modern day GPU resulting in a substantial performance increase. We believe that our system is the first ever completely GPU based agent simulation framework. Although GPUs are the focus of our current implementations, our techniques can easily be adapted to other data-parallel architectures. We have benchmarked our framework against contemporary toolkits using two popular ABMs, namely, SugarScape and StupidModel.GPGPU, Agent Based Modeling, Data Parallel Algorithms, Stochastic Simulations

iCanCloud: a flexible and scalable cloud infrastructure simulator

Simulation techniques have become a powerful tool for deciding the best starting conditions on pay-as-you-go scenarios. This is the case of public cloud infrastructures, where a given number and type of virtual machines (in short VMs) are instantiated during a specified time, being this reflected in the final budget. With this in mind, this paper introduces and validates iCanCloud, a novel simulator of cloud infrastructures with remarkable features such as flexibility, scalability, performance and usability. Furthermore, the iCanCloud simulator has been built on the following design principles: (1) it's targeted to conduct large experiments, as opposed to others simulators from literature; (2) it provides a flexible and fully customizable global hypervisor for integrating any cloud brokering policy; (3) it reproduces the instance types provided by a given cloud infrastructure; and finally, (4) it contains a user-friendly GUI for configuring and launching simulations, that goes from a single VM to large cloud computing systems composed of thousands of machines.This research was partially supported by the following projects: Spanish MEC project TESIS (TIN2009-14312-C02-01), and Spanish Ministry of Science and Innovation under the grant TIN2010-16497.Publicad

Hierarchical architecture design and simulation environment

The Hierarchical Architectural design and Simulation Environment (HASE)is intended as a flexible tool for computer architects who wish to experiment with alternative architectural configurations and design parameters. HASE is both a design environment and a simulator. Architecture components are described by a hierarchical library of objects defined in terms of an object oriented simulation language. HASE instantiates these objects to simulate and animate the execution of a computer architecture. An event trace generated by the simulator therefore describes the interaction between architecture components, for example, fetch stages, address and data buses, sequencers, instruction buffers and register files. The objects can model physical components at different abstraction levels, eg. PMS (processor memory switch), ISP (instruction set processor) and RTL (register transfer level). HASE applies the concepts of inheritance, encapsulation and polymorphism associated with object orientation, to simplify the design and implementation of an architecture simulation that models component operations at different abstraction levels. For example, HASE can probe the performance of a processor's floating point unit, executing a multiplication operation, at a lower level of abstraction, i.e. the RTL, whilst simulating remaining architecture components at a PMS level of abstraction. By adopting this approach, HASE returns a more meaningful and relevant event trace from an architecture simulation. Furthermore, an animator visualises the simulation's event trace to clarify the collaborations and interactions between architecture components. The prototype version of HASE is based on GSS (Graphical Support System), and DEMOS (Discrete Event Modelling On Simula)

Couplers for linking environmental models: scoping study and potential next steps

This report scopes out what couplers there are available in the hydrology and atmospheric modelling fields. The work reported here examines both dynamic runtime and one way file based coupling. Based on a review of the peer-reviewed literature and other open sources, there are a plethora of coupling technologies and standards relating to file formats. The available approaches have been evaluated against criteria developed as part of the DREAM project. Based on these investigations, the following recommendations are made: • The most promising dynamic coupling technologies for use within BGS are OpenMI 2.0 and CSDMS (either 1.0 or 2.0) • Investigate the use of workflow engines: Trident and Pyxis, the latter as part of the TSB/AHRC project “Confluence” • There is a need to include database standards CSW and GDAL and use data formats from the climate community NetCDF and CF standards. • Development of a “standard” composition which will consist of two process models and a 3D geological model all linked to data stored in the BGS corporate database and flat file format. Web Feature Services should be included in these compositions. There is also a need to investigate other approaches in different disciplines: The Loss Modelling Framework, OASIS-LMF is the best candidate

Sharing memory in distributed systems

We propose an algorithm for simulating atomic registers, test-and-set, fetch-and-add, and read-modify-write registers in a message passing system. The algorithm is fault tolerant and works correctly in presence of up to (N/2) -1 node failures where N is the number of processors in the system. The high resilience of the algorithm is obtained by using randomized consensus algorithms and a robust communication primitive. The use of this primitive allows a processor to exchange local information with a majority of processors in a consistent way, and therefore to take decisions safely. The simulator makes it possible to translate algorithms for the shared memory model to that for the message passing model. With some minor modifications the algorithm can be used to robustly simulate shared queues, shared stacks, etc. (Abstract shortened with permission of author.)